Moving Object Detection Algorithm Research Articles

Moving Object Detection for Real Time Video Surveillance: An Edge Based Approach

SUMMARY This paper presents an automatic edge segment based algorithm for the detection of moving objects that has been specially developed to deal with the variations in illumination and contents of background. We investigated the suitability of the proposed edge segment based moving object detection algorithm in comparison with the traditional intensity based as well as edge pixel based detection methods. In our method, edges are extracted from video frames and are represented as segments using an efficiently designed edge class. This representation helps to obtain the geometric information of edge in the case of edge matching and shape retrieval; and creates effective means to incorporate knowledge into edge segment during background modeling and motion tracking. An efficient approach for background edge generation and a robust method of edge matching are presented to effectively reduce the risk of false alarm due to illumination change and camera motion while maintaining the high sensitivity to the presence of moving object. The proposed method can be successfully realized in video surveillance applications in home networking environment as well as various monitoring systems. As, video coding standard MPEG-4 enables content based functionality, it can successfully utilize the shape information of the detected moving objects to achieve high coding efficiency. Experiments with real image sequences, along with comparisons with some other existing methods are presented, illustrating the robustness of the pro

Moving object detection algorithm inspired by the sequence detection in the hippocampus and its digital LSI implementation

We propose a high-speed moving object detection algorithm based on parallel processing inspired by the mechanism for sequence detection in neural networks such as the hippocampal CA3 region. Computer simulations verified that the present algorithm performs well. A digital LSI architecture for the moving object detection and a modified algorithm suitable for LSI implementation are also proposed. Correct logical operation was verified using a logic simulator and the algorithm was implemented on an FPGA board.

Tracking Object Movement via Two Stage Median Operation and State Transition Diagram under Various Light Conditions

A moving object detection algorithm for surveillance video is here proposed which employs background initialization based on two-stage median filtering and a background updating method based on state transition diagram.BR In the background initialization, the spatiotemporal similarity is measured in the subinterval. From the accumulated difference between the base frame and the other frames in a subinterval, the regions affected by moving objects are located. The median is applied over the subsequence in the subinterval in which regions share similarity. The outputs from each subinterval are filtered by a two-stage median filter.BR The background of every frame is updated by the suggested state transition diagram. The object is detected by the difference between the current frame and the updated background.BR The proposed method showed good results even for busy, crowded sequences which included moving objects from the first frame.